Unified XML Indexing With Single-Scan Semi-Structured Queries
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Solution Overview
Problem
Existing database management systems (DBMS) face inefficiencies when indexing semi-structured data due to the need for multiple scans and resource-intensive index maintenance, especially when data is updated, and traversing indexes is costly.
Innovation Solution
A single-scan indexing method for semi-structured data in DBMS that generates efficient index data structures using event-based scanning, path-based and node value-based indexing, and document bitmaps to optimize text and path-based range search queries.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If multiple indexes are maintained for different query types on semi-structured data, then query flexibility and access speed are improved, but computing resource consumption and index maintenance complexity increase
Solution Approach 1:
The patent combines multiple indexing approaches (full-text indexing, path-based indexing, and value-based indexing) into a unified indexing system that operates on semi-structured data in a single scan. This merging eliminates the need for separate indexing processes while maintaining the ability to support various query types efficiently.
Solution Approach 2:
The unified index structure serves multiple functions simultaneously: it supports full-text searches, path-based queries, and value-based filtering. The index is designed to be versatile, handling different query patterns without requiring separate specialized indexes, thereby reducing overall resource consumption.
2Adaptability or versatility
If multiple scans are performed on semi-structured data for different query types, then comprehensive data access is achieved, but processing time and resource intensity increase
Solution Approach 1:
The patent performs preliminary action by conducting a single comprehensive scan of the semi-structured data during the indexing phase, extracting and organizing all relevant information (text content, path structures, and node values) into a unified index. This preliminary processing eliminates the need for subsequent repeated scans when executing queries, significantly reducing processing time.
3Measurement precision
If path-based indexes are traversed and column stores are scanned to filter query results, then accurate query results are obtained, but computing resources are wasted on retrieving and scanning non-matching data
Solution Approach 1:
The patent applies local quality by organizing index data according to its specific characteristics: text content is indexed for full-text searches, path structures are indexed for hierarchical queries, and node values are indexed for filtering operations. This localized optimization allows the system to directly access relevant data segments without scanning unrelated data, improving both accuracy and efficiency.
Data Source
AI summary
Techniques are described for unified indexing of semi-structured data. In an embodiment, a database management system (DBMS) stores a number of semi-structured data documents in its tables. Such documents include section(s) of nodes arranged in a hierarchy, having a root node and one or more leaf nodes. DBMS may receive a query specifying a path expression for the documents. Based on the path expression, the DBMS generates a query path identifier. The query path identifier is used as a lookup into the index store to determine that the query path identifier is a section path identifier for a partial hierarchical path. If so, the DBMS retrieves from the identified document at least one result node by evaluating nodes hierarchically belonging to the particular root node according to the query.